The fayherriot command for estimating small-area indicators

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Abstract

We introduce a command, fayherriot, that implements the Fay– Herriot model (Fay and Herriot, 1979, Journal of the American Statistical Association 74: 269–277), which is a small-area estimation technique (Rao and Molina, 2015, Small Area Estimation), in Stata. The Fay–Herriot model improves the precision of area-level direct estimates using area-level covariates. It belongs to the class of linear mixed models with normally distributed error terms. The fayherriot command encompasses options to a) produce out-of-sample predictions, b) adjust nonpositive random-effects variance estimates, and c) deal with the violation of model assumptions.

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Halbmeier, C., Kreutzmann, A. K., Schmid, T., & Schröder, C. (2019). The fayherriot command for estimating small-area indicators. Stata Journal, 19(3), 626–644. https://doi.org/10.1177/1536867X19874238

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